Biology subjects

Sethna, J. P.

Publications and source records attributed to Sethna, J. P..

4 recordsLinked to original sources

bioRxiv2026

Shear Strain Stiffening in Cartilage is Governed by a Mechanical Phase Transition

Large shear deformation in cartilage can lead to tissue failure and injury, which are often precursors to diseases such as post-traumatic osteoarthritis. Under shear, cartilage strain-stiffens prior to failure, which makes stiffening an important indicator of changes to the loading of the extracellular matrix that gives rise to this tissue's properties. While a variety of stiffening mechanisms ranging from uncrimping to fiber-alignment have been explored, whether such mechanisms apply to the depth dependent shear strain stiffening in articular cartilage remains poorly understood. Here, we present experiments and theory that support the idea that the strain-stiffening behavior is caused by a mechanical phase transition from a random isotropic network whose mechanics arise primarily from bending-dominated modes to one where the mechanics arise from stretching-dominated modes. Indeed, consistent with network model predictions, we find that stress-strain data for all depths can be collapsed onto a single universal curve that diverges at a depth-dependent critical strain. These results show that increasing the local concentration of collagen, which constitutes the primary load-bearing network in cartilage, decreases the critical strain at which the strain-stiffening transition occurs, while increasing the low-strain elastic modulus. Furthermore, we demonstrate that bulk compression leads to a higher critical strain and decreased low-strain elastic modulus. Network simulations capture this rich behavior, and indicate that under compression the network collapses, which allows for larger strains before the transition from bending-dominated to stretching-dominated mechanics occurs. Collectively, these findings shed light on the roles that tissue composition and axial strain play in the mechanisms that organize how articular cartilage stiffens during the lead-up to injury.

biophysics↗

bioRxiv2026

Partition Coefficients Reveal Changes in Properties of Low-Contrast Biomolecular Condensates

Biomolecular condensates are domains within cells with distinct compositions, held together by intermolecular cohesion. They are implicated in a variety of cellular processes, and in vitro studies have revealed the molecular driving forces that underly their condensation. However, in vitro condensates do not capture essential features of cellular condensates. In particular, enrichment of proteins, quantified by partition coefficients, is often exaggerated in these simplified systems. We show that the addition of free amino acids and other small molecules to model condensates can bring their partition coefficients within physiological range. In this limit, where there is low biochemical contrast between condensates and their surroundings, we observe striking changes to condensate behavior. Such low-contrast condensates exhibit large fluctuations in shape and composition and show enhanced sensitivity to changes in their environment. These behaviors reflect dramatic shifts to their material properties, including interfacial tension, rheology, and chemical susceptibilities. We note remarkable similarities in these effects across seemingly unrelated two-phase fluid systems. To explain these trends, we reformulate classic models of critical phenomena in terms of partition coefficients. This framework simplifies application of theory to experiments with near-critical fluids and suggests new experimental approaches for assessing condensate physiology in live cells.

biophysics↗

bioRxiv2026

The hippocampus as a small-world cognitive map

When a mouse perceives a hawks shadow, it may have only seconds to decide where to run, yet the safest refuge is often neither visible nor nearby. To survive, it must search its cognitive map quickly enough to choose among many possibilities, and accurately enough to avoid dead ends and hazards along the way, all while what counts as "safe" changes as paths, refuges, and threats shift with time. This scenario highlights a core design problem: cognitive maps must preserve fine local structure for reliable action, yet remain globally searchable so that distant, useful solutions can be found efficiently in both space and time. The hippocampus is thought to support such maps, with population activity representing world states and their transitions--yet how these maps are structured to solve this design problem is not well understood. Here, we used a novel geometry-aware autoencoder to model the structure of the cognitive map from longitudinal calcium imaging from thousands of hippocampal CA1 neurons in mice learning a memory-guided navigation task. We discovered that the hippocampal population code achieves both local fidelity and global searchability through small-world network structure in the space of neural representations that leverages two complementary mechanisms. At the population level, helical (rotation-plus-drift) dynamics of neural representations relative to past experience build new maps that preserve local information about nearby positions in space and time while remaining distinguishable from earlier representations. At the cellular level, neurons with coordinated multi-field activity create sparse, long-range shortcuts between distant representations. During synchronous population events in immobility, decoded activity often jumps to distant states in space, time, and task conditions, suggesting these shortcuts are engaged during offline processing. This functional organization, with implications for both neuroscience and artificial intelligence, sheds light on how hippocampal representations may be optimized for a fundamental challenge faced by intelligent systems: efficiently searching through accurate internal models of the world.

neuroscience↗

bioRxiv2024

Torsional Mechanics of Circular DNA

Circular DNA found in the cell is actively regulated to an underwound state, with their superhelical density close to{sigma} [~] - 0.06. While this underwound state is essential to life, how it impacts the torsional mechanical properties of DNA is not fully understood. In this work, we performed simulations to understand the torsional mechanics of circular DNA and validated our results with single-molecule measurements and analytical theory. We found that the torque generated at{sigma} [~] - 0.06 is near but slightly below that required to melt DNA, significantly decreasing the energy barrier for proteins that interact with melted DNA. Furthermore, supercoiled circular DNA experiences force (tension) and torque that are equally distributed through the DNA contour. We have also extended a previous analytical framework to show how the plectonemic twist persistence length depends on the intrinsic bending persistence length and twist persistence length. Our work establishes a framework for understanding DNA supercoiling and torsional dynamics of circular DNA.

biophysics↗